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The Geometric-VaR Backtesting Method

Author

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  • Denis Pelletier
  • Wei Wei

Abstract

This article develops a new test to evaluate value-at-risk (VaR) forecasts. VaR is a standard risk measure widely utilized by financial institutions and regulators, yet estimating VaR is a challenging problem, and popular VaR forecast relies on unrealistic assumptions. Hence, assessing the performance of VaR is of great importance. We propose the geometric-VaR test which utilizes the duration between the violations of VaR as well as the value of VaR. We conduct a Monte Carlo study based on desk-level data and we find that our test has high power against various alternatives.

Suggested Citation

  • Denis Pelletier & Wei Wei, 2016. "The Geometric-VaR Backtesting Method," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 725-745.
    • Handle: RePEc:oup:jfinec:v:14:y:2016:i:4:p:725-745.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbv015
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    References listed on IDEAS

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    1. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-679, June.
    2. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Finance, Presses universitaires de Grenoble, vol. 33(1), pages 79-112.
    3. Bontemps, Christian, 2014. "Simple moment-based tests for value-at-risk models and discrete distribution," TSE Working Papers 14-535, Toulouse School of Economics (TSE).
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    Cited by:

    1. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    2. Taylor, James W., 2020. "A strategic predictive distribution for tests of probabilistic calibration," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1380-1388.
    3. Tu, Anthony H. & Chen, Cathy Yi-Hsuan, 2018. "A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 243-268.
    4. S. M. Masrur Ahmed, 2023. "Sizing Strategies for Algorithmic Trading in Volatile Markets: A Study of Backtesting and Risk Mitigation Analysis," Papers 2309.09094, arXiv.org, revised Sep 2023.
    5. Marta Małecka, 2021. "Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 145-162, March.
    6. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    7. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    8. Małecka Marta, 2021. "Testing for a serial correlation in VaR failures through the exponential autoregressive conditional duration model," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 145-162, March.

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